Calculating Potential Energy Curves With Quantum Monte Carlo

Powell, Andrew D.

Permalink

https://hdl.handle.net/2142/50955 Copy

Description

Title

Calculating Potential Energy Curves With Quantum Monte Carlo

Author(s)

Powell, Andrew D.

Contributor(s)

Dawes, Richard

Issue Date

2014-06-19

Keyword(s)

Fundamental interest

Abstract

Quantum Monte Carlo (QMC) is a computational technique that can be applied to the electronic Schrödinger equation for molecules. QMC methods such as Variational Monte Carlo (VMC) and Diffusion Monte Carlo (DMC) have demonstrated the capability of capturing large fractions of the correlation energy, thus suggesting their possible use for high-accuracy quantum chemistry calculations. QMC methods scale particularly well with respect to parallelization making them an attractive consideration in anticipation of next-generation computing architectures which will involve massive parallelization with millions of cores. Due to the statistical nature of the approach, in contrast to standard quantum chemistry methods, uncertainties (error-bars) are associated with each calculated energy. This study focuses on the cost, feasibility and practical application of calculating potential energy curves for small molecules with QMC methods. Trial wave functions were constructed with the multi-configurational self-consistent field (MCSCF) method from GAMESS-US.[1] The CASINO Monte Carlo quantum chemistry package [2] was used for all of the DMC calculations. An overview of our progress in this direction will be given. References: M. W. Schmidt et al. J. Comput. Chem. 14, 1347 (1993). R. J. Needs et al. J. Phys.: Condensed Matter 22, 023201 (2010).

Publisher

International Symposium on Molecular Spectroscopy

Type of Resource

text

Language

English

Permalink

http://hdl.handle.net/2142/50955

DOI

https://doi.org/10.15278/isms.2014.RD03

Copyright and License Information

Copyright 2014 by the authors. Licensed under a Creative Commons Attribution 4.0 International License. http://creativecommons.org/licenses/by/4.0/

Owning Collections